Digital Health for Lumbar Degeneration (NCT07133724) | Clinical Trial Compass
RecruitingNot Applicable
Digital Health for Lumbar Degeneration
Taiwan100 participantsStarted 2025-08-01
Plain-language summary
This study will integrate wireless wearable sensors, smartphone imaging, and multimodal artificial intelligence (AI) to address the rehabilitation needs of patients with lumbar degeneration. Patients will undergo comprehensive functional assessments, and individualized exercise instruction with real-time feedback will be provided through a smartphone application. The goals of this research are to: (1) develop a multimodal AI-based digital health system combining IMU sensors and smartphone cameras for real-time assessment and interactive rehabilitation training, (2) construct biomechanics- and gait-analysis models to support personalized rehabilitation for patients with lumbar degeneration, and (3) investigate the mechanisms and clinical efficacy of pelvic control exercise training combined with real-time smartphone feedback in improving function and quality of life for aging patients.
Who can participate
Age range50 Years – 80 Years
SexALL
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Inclusion criteria
✓. Age between 50-80 years to capture the typical characteristics of lumbar degeneration in this age group.
✓. No history of low back pain lasting more than one week or severe enough to interrupt work within the past year.
✓. Normal lumbar functional mobility.
✓. Ability to walk independently for more than 10 meters.
Exclusion criteria
✕. Presence of systemic joint diseases such as ankylosing spondylitis, rheumatoid arthritis, or multiple sclerosis, which may significantly affect lumbar mobility and gait patterns.
✕. Central nervous system disorders (e.g., spinal cord injury, stroke, or Parkinson's disease) that may influence gait and motor control.
✕. Vestibular system disorders, to avoid balance abnormalities interfering with gait testing.
✕. History of spinal or lower limb surgery, as postoperative changes may affect the accuracy of gait data.